update README (#3840)

PaddleSpeech/DeepASR/README.md

@@ -7,15 +7,15 @@ The minimum PaddlePaddle version needed for the code sample in this directory is
 DeepASR (Deep Automatic Speech Recognition) is a speech recognition system based on PaddlePaddle FLuid and Kaldi. It uses the Fluid framework to perform the configuration and training of acoustic models in speech recognition and integrates Kaldi decoder. It is designed to facilitate Kaldi users to implement the rapid and large-scale training of acoustic models, and to use Kaldi to complete complex speech data preprocessing and final decoding processes.
 
 ### Content
-- [Introduction](#Introduction)
-- [Installation](#Installation)
-- [Data reprocessing](#Data reprocessing)
-- [Training](#Training)
-- [Perf profiling](#Perf profiling)
-- [Inference & Decoding](#Inference & Decoding)
-- [Scoring error rate](#Scoring error rate)
-- [Aishell example](#Aishell example)
-- [Question and Contribution](#Question and Contribution)
+- [Introduction](#introduction)
+- [Installation](#installation)
+- [Data reprocessing](#data-reprocessing)
+- [Training](#training)
+- [Perf profiling](#perf-profiling)
+- [Inference and Decoding](#inference-and-decoding)
+- [Scoring error rate](#scoring-error-rate)
+- [Aishell example](#aishell-example)
+- [Question and Contribution](#question-and-contribution)
 
 
 ### Introduction
@@ -84,7 +84,7 @@ CUDA_VISIBLE_DEVICES=0 python -u tools/profile.py \
                    --mean_var global_mean_var
 ```
 
-### Inference & Decoding
+### Inference and Decoding
 After fully training the acoustic model, using the model checkpoint saved in the training process, the input audio data can be decoded and output, and the sound to text recognition result can be obtained.
 
 ```

PaddleSpeech/DeepASR/README_cn.md

@@ -14,7 +14,7 @@ DeepASR (Deep Automatic Speech Recognition) 是一个基于PaddlePaddle FLuid与
 - [训练过程中的时间分析](#训练过程中的时间分析)
 - [预测和解码](#预测和解码)
 - [错误率评估](#错误率评估)
-- [Aishell 实例](#Aishell 实例)
+- [Aishell 实例](#aishell-实例)
 - [欢迎贡献更多的实例](#欢迎贡献更多的实例)
 
 ### 模型概览